What is predictive segmentation?

Predictive segmentation is a platform capability used to predict the future behavior of a customer with high certainty based on their past behavior.

It allows marketers to encourage certain customer actions or prevent undesirable tendencies.

By analyzing large amounts of customer data, marketers can target their messaging more effectively and optimize campaigns for maximum efficiency.

Predictive segmentation can also help automate decisions like budget allocation, content delivery, and personalization based on customer behavior. This helps marketers leverage data to deliver more relevant experiences for customers and, ultimately, increase retention, loyalty and revenue.

What are the four different types of audience segmentation?

Demographic segmentation:
Involves segmenting customers by age, gender, location, income, education level and other demographic factors.

Psychographic segmentation:
Aims to categorize people by their values, attitudes, interests and lifestyles. It helps marketers identify what motivates customers and tailor messaging accordingly.

Behavioral segmentation:
Divides customers based on their past behavior such as purchase history and engagement with the brand’s marketing efforts.

Social media segmentation:
Helps identify groups of customers that are likely to engage with social media campaigns or respond to specific types of content posted on social media channels.

How do predictive segments work?

Predictive segments (sometimes called AI segments) use prediction scores to calculate how likely it is that a contact will perform an action, for example, whether a customer will convert, remain inactive or churn.

Predictive segments allow marketers to predict the future behavior of their customers with high certainty based on past behavior. This allows marketers to encourage customer actions or prevent undesirable tendencies.

What are the benefits of predictive segments?

Predictive segments allow marketers to:

  • Target contacts with emails having different subject lines or content based on your customers’ engagement levels.
  • Spare money on CRM Ads by targeting only those contacts who are likely to remain inactive or disengage or by targeting these contacts on different channels.
  • Lead your customers from one lifecycle stage to another more precisely and efficiently, for example, you can encourage your first-time buyers to become active buyers.
  • Differentiate your leads who are likely to convert from those who are likely to remain inactive or become cold.
  • Distinguish your customers who are likely to engage with your campaigns from those who are likely to remain active or disengage.

Predictive segmentation with Emarsys

Emarsys works with leading brands like PUMA, Pizza Hut and Nike to increase acquisition, purchase frequency, average order value and retention by using a rich set of customer, sales and product data to power predictive segmentation.